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Machine Learning

Detect Threats Other Solutions Miss

Detecting attacks is essential to protecting business reputations, revenue, and opportunities. Malicious actors often hide from traditional security solutions within network traffic, but finding these attacks is an enormous hurdle for IT security teams.

MENDEL uses advanced teachable unsupervised machine learning as part of its network traffic analysis-based approach to these attacks.

Why Machine Learning

Faster detection of unknown threats and anomalies

Reduction of time-to-response security incidents

More sensitive and reliable behavioral detection

Behavioral detection adapts to changing environment

Less time demanding administration

Adaptation, not baselines

Many analytic security tools rely on pre-set rules or baselines to detect threats. MENDEL independently models the network’s unique traffic patterns from the moment it’s installed. This model adapts as traffic and threats in the network evolve, to effectively pinpoint malicious and anomalous behavior. Based on MENDEL's Advanced Security Network Metrics data, the model is able to identify subtle changes in network traffic caused by malicious actors. This allows it to detect threats more effectively than security tools that use pre-set rules or baselines.

Unsupervised machine learning, that can be taught

Machine learning is effective in detecting threats, and becomes more effective over time. But it can generate a high number of false positives as it learns, creating challenges for network security teams. Truly effective machine learning can be taught by an analyst. MENDEL's machine learning is advanced on its own, but is also teachable, making it a truly effective and useful for the security analyst.

Even more advanced detection

MENDEL’s advanced machine learning algorithms apply several unique analytic techniques to each flow, allowing it to identify threats which seek to deceive a basic network performance model; including the ability to detect presence of anomalous devices, communication volume, communication peers. MENDEL is also unique in that it distinguishes between human and machine communication to identify dangerous advanced threats which are hidden within the network, unseen by other security solutions.

MENDEL also identifies personally identifying information within network communications, as well as unauthorized access to personal data, making it ideal for those implementing GDPR-focused
security postures.